Disco Diffusion
Contents
Disco Diffusion#
This is an simple way of creating compelling Disco Diffusion artworks for generative artists.
References:#
Prepare an environment#
from ekorpkit import eKonf
eKonf.setLogger("WARNING")
eKonf.set_cuda(device=4)
print("version:", eKonf.__version__)
is_notebook = eKonf.is_notebook()
is_colab = eKonf.is_colab()
print("is notebook?", is_notebook)
print("is colab?", is_colab)
if is_colab:
eKonf.mount_google_drive(
workspace="MyDrive/colab_workspace", project="disco-imagen"
)
print("environment variables:")
eKonf.print(eKonf.env().dict())
INFO:ekorpkit.base:Setting cuda device to ['A100-SXM4-40GB (id:4)']
version: 0.1.38+31.geec37f8.dirty
is notebook? True
is colab? False
environment variables:
{'CUDA_DEVICE_ORDER': 'PCI_BUS_ID',
'CUDA_VISIBLE_DEVICES': '4',
'EKORPKIT_CONFIG_DIR': '/workspace/projects/ekorpkit-book/config',
'EKORPKIT_DATA_DIR': None,
'EKORPKIT_LOG_LEVEL': 'WARNING',
'EKORPKIT_PROJECT': 'ekorpkit-book',
'EKORPKIT_WORKSPACE_ROOT': '/workspace',
'KMP_DUPLICATE_LIB_OK': 'TRUE',
'NUM_WORKERS': 230}
Create a disco instance#
cfg = eKonf.compose("model/disco")
disco = eKonf.instantiate(cfg)
print(f"Version: {disco.version}")
INFO:ekorpkit.base:Loaded .env from /workspace/projects/ekorpkit-book/config/.env
INFO:ekorpkit.base:setting environment variable CACHED_PATH_CACHE_ROOT to /workspace/.cache/cached_path
INFO:ekorpkit.base:setting environment variable KMP_DUPLICATE_LIB_OK to TRUE
Setting up [LPIPS] perceptual loss: trunk [vgg], v[0.1], spatial [off]
Loading model from: /opt/conda/lib/python3.8/site-packages/lpips/weights/v0.1/vgg.pth
Version: v5.61
Image only mode#
disco.config.models.openclip_models.RN101_quickgelu_yfcc15m = True
disco.config.models.diffusion_model = "watercolordiffusion"
eKonf.print(disco.config.models)
# If you change model configs, you have to reload models
disco.load_models()
{'clip_models': {'RN101': False,
'RN50': False,
'RN50x16': False,
'RN50x4': False,
'RN50x64': False,
'ViTB16': True,
'ViTB32': True,
'ViTL14': False,
'ViTL14_336px': False},
'custom_model': 'ema_0.9999_058000.pt',
'diffusion_model': 'watercolordiffusion',
'openclip_models': {'RN101_quickgelu_yfcc15m': True,
'RN101_yfcc15m': False,
'RN50_cc12m': True,
'RN50_quickgelu_cc12m': False,
'RN50_quickgelu_yfcc15m': False,
'RN50_yffcc15m': False,
'ViTB16_laion400m_e31': False,
'ViTB16_laion400m_e32': False,
'ViTB32_laion2b_e16': False,
'ViTB32_laion400m_e31': False,
'ViTB32_laion400m_e32': True,
'ViTB32quickgelu_laion400m_e31': False,
'ViTB32quickgelu_laion400m_e32': False}}
Setting up [LPIPS] perceptual loss: trunk [vgg], v[0.1], spatial [off]
Loading model from: /opt/conda/lib/python3.8/site-packages/lpips/weights/v0.1/vgg.pth
text_prompts = "A beautiful water painting of Jeju Island."
batch_name = "jeju"
results = disco.imagine(
text_prompts,
batch_name=batch_name,
n_samples=2,
steps=200,
show_collage=True,
diffusion_sampling_mode='ddim',
clip_guidance_scale=7500,
use_secondary_model=False,
)
results
{'image_filepaths': ['/workspace/projects/ekorpkit-book/disco-imagen/outputs/disco-diffusion/jeju/jeju(7)_0000.png',
'/workspace/projects/ekorpkit-book/disco-imagen/outputs/disco-diffusion/jeju/jeju(7)_0001.png'],
'config_file': 'jeju(7)_settings.yaml',
'config': {'animation_mode': 'None',
'batch_name': 'jeju',
'display_rate': 20,
'n_samples': 2,
'batch_size': 1,
'resume_run': False,
'run_to_resume': 'latest',
'resume_from_frame': 'latest',
'retain_overwritten_frames': True,
'diffusion_sampling_mode': 'ddim',
'use_secondary_model': False,
'steps': 200,
'width_height': [512, 448],
'width_height_for_512x512_models': [1280, 768],
'width_height_for_256x256_models': [512, 448],
'clip_guidance_scale': 7500,
'tv_scale': 0,
'range_scale': 150,
'sat_scale': 0,
'cutn_batches': 4,
'skip_augs': False,
'init_image': 'None',
'init_scale': 1000,
'skip_steps': 10,
'frames_scale': 1500,
'frames_skip_steps': '60%',
'video_init_steps': 100,
'video_init_clip_guidance_scale': 1000,
'video_init_tv_scale': 0.1,
'video_init_range_scale': 150,
'video_init_sat_scale': 300,
'video_init_cutn_batches': 4,
'video_init_skip_steps': 50,
'video_init_file': 'init.mp4',
'video_init_path': '/workspace/projects/ekorpkit-book/disco-imagen/init_images/init.mp4',
'extract_nth_frame': 2,
'persistent_frame_output_in_batch_folder': True,
'video_init_seed_continuity': False,
'video_init_flow_warp': True,
'video_init_flow_blend': 0.999,
'video_init_check_consistency': False,
'video_init_blend_mode': 'optical flow',
'video_init_frames_scale': 15000,
'video_init_frames_skip_steps': '70%',
'force_flow_generation': False,
'key_frames': True,
'max_frames': 1,
'interp_spline': 'Linear',
'angle': '0:(0)',
'zoom': '0: (1), 10: (1.05)',
'translation_x': '0: (0)',
'translation_y': '0: (0)',
'translation_z': '0: (10.0)',
'rotation_3d_x': '0: (0)',
'rotation_3d_y': '0: (0)',
'rotation_3d_z': '0: (0)',
'midas_depth_model': 'dpt_large',
'midas_weight': 0.3,
'near_plane': 200,
'far_plane': 10000,
'fov': 40,
'padding_mode': 'border',
'sampling_mode': 'bicubic',
'turbo_mode': False,
'turbo_steps': '3',
'turbo_preroll': 10,
'vr_mode': False,
'vr_eye_angle': 0.5,
'vr_ipd': 5.0,
'intermediate_saves': [],
'steps_per_checkpoint': None,
'intermediates_in_subfolder': True,
'perlin_init': False,
'perlin_mode': 'mixed',
'set_seed': 'random_seed',
'eta': 0.8,
'clamp_grad': True,
'clamp_max': 0.05,
'randomize_class': True,
'clip_denoised': False,
'fuzzy_prompt': False,
'rand_mag': 0.05,
'cut_overview': '[14]*200+[12]*200+[4]*400+[0]*200',
'cut_innercut': '[2]*200+[4]*200+[12]*400+[12]*200',
'cut_ic_pow': '[12]*300+[12]*100+[12]*50+[12]*50+[10]*100+[10]*100+[10]*300',
'cut_icgray_p': '[0.7]*100+[0.6]*100+[0.45]*100+[0.3]*100+[0]*600',
'pad_or_pulp_cut_overview': '[15]*100+[15]*100+[12]*100+[12]*100+[6]*100+[4]*100+[2]*200+[0]*200',
'pad_or_pulp_cut_innercut': '[1]*100+[1]*100+[4]*100+[4]*100+[8]*100+[8]*100+[10]*200+[10]*200',
'pad_or_pulp_cut_ic_pow': '[12]*300+[12]*100+[12]*50+[12]*50+[10]*100+[10]*100+[10]*300',
'pad_or_pulp_cut_icgray_p': '[0.87]*100+[0.78]*50+[0.73]*50+[0.64]*60+[0.56]*40+[0.50]*50+[0.33]*100+[0.19]*150+[0]*400',
'watercolor_cut_overview': '[14]*200+[12]*200+[4]*400+[0]*200',
'watercolor_cut_innercut': '[2]*200+[4]*200+[12]*400+[12]*200',
'watercolor_cut_ic_pow': '[12]*300+[12]*100+[12]*50+[12]*50+[10]*100+[10]*100+[10]*300',
'watercolor_cut_icgray_p': '[0.7]*100+[0.6]*100+[0.45]*100+[0.3]*100+[0]*600',
'use_vertical_symmetry': False,
'use_horizontal_symmetry': False,
'transformation_percent': [0.09],
'video_output': {'skip_video_for_run_all': False,
'blend': 0.5,
'video_init_check_consistency': False,
'init_frame': 1,
'last_frame': 'final_frame',
'fps': 12,
'view_video_in_cell': False},
'models': {'diffusion_model': 'watercolordiffusion',
'clip_models': {'ViTB32': True,
'ViTB16': True,
'ViTL14': False,
'ViTL14_336px': False,
'RN50x4': False,
'RN50x16': False,
'RN50x64': False,
'RN50': False,
'RN101': False},
'openclip_models': {'ViTB32_laion2b_e16': False,
'ViTB32_laion400m_e31': False,
'ViTB32_laion400m_e32': True,
'ViTB32quickgelu_laion400m_e31': False,
'ViTB32quickgelu_laion400m_e32': False,
'ViTB16_laion400m_e31': False,
'ViTB16_laion400m_e32': False,
'RN50_yffcc15m': False,
'RN50_cc12m': True,
'RN50_quickgelu_yfcc15m': False,
'RN50_quickgelu_cc12m': False,
'RN101_yfcc15m': False,
'RN101_quickgelu_yfcc15m': True},
'custom_model': 'ema_0.9999_058000.pt'},
'text_prompts': {0: ['A beautiful water painting of Jeju Island.']},
'image_prompts': None,
'batch_num': 7,
'stop_on_next_loop': False,
'side_x': 512,
'side_y': 448,
'calc_frames_skip_steps': 120,
'start_frame': 0,
'start_sample': 0,
'seed': 2792322357,
'show_collage': True,
'show_losses': False},
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...]}
3D animation mode#
text_prompts = {
0: "A beautiful new world in Jeju, artstation matte painting.",
100: "Beautiful mountains in Jeju, artstation matte painting.",
300: "A beautiful sea in Jeju, artstation matte painting.",
500: "A beautiful woman in Jeju, artstation matte painting.",
700: "A beautiful wind in Jeju, artstation matte painting.",
900: "A beautiful new world in Jeju, artstation matte painting.",
}
batch_name = "newworld-3d"
disco.imagine(
text_prompts,
batch_name=batch_name,
batch_num=11,
resume_run=True,
steps=300,
animation_mode="3D",
rotation_3d_z="0: (0), 500: (1), 600: (-1)",
# perlin_init=True,
# perlin_mode="color",
diffusion_sampling_mode='ddim',
max_frames = 5000,
width_height = [768, 512],
clip_guidance_scale=7500,
)
INFO:ekorpkit.models.disco.base:translation_x: 0.0
INFO:ekorpkit.models.disco.base:translation_y: 0.0
INFO:ekorpkit.models.disco.base:translation_z: 10.0
INFO:ekorpkit.models.disco.base:rotation_3d_x: 0.0
INFO:ekorpkit.models.disco.base:rotation_3d_y: 0.0
INFO:ekorpkit.models.disco.base:rotation_3d_z: -0.6799999999999999
INFO:ekorpkit.models.disco.base:translation: [-0.0, 0.0, -0.05]
INFO:ekorpkit.models.disco.base:rotation: [0.0, 0.0, -0.6799999999999999]
INFO:ekorpkit.models.disco.base:rot_mat: tensor([[[ 1.0000, 0.0119, 0.0000],
[-0.0119, 1.0000, 0.0000],
[ 0.0000, 0.0000, 1.0000]]], device='cuda:4')
INFO:ekorpkit.models.disco.disco_xform_utils:Running AdaBins depth estimation implementation...
Loading base model ()...
Using cache found in /root/.cache/torch/hub/rwightman_gen-efficientnet-pytorch_master
Done.
Removing last two layers (global_pool & classifier).
Building Encoder-Decoder model..Done.
INFO:ekorpkit.models.disco.disco_xform_utils:Running MiDaS depth estimation implementation...
2D animation mode#
text_prompts = "Brave and beautiful new world in Jeju, artstation matte painting."
batch_name = "newworld-2d"
disco.imagine(
text_prompts,
batch_name=batch_name,
steps=300,
animation_mode = '2D',
# rotation_3d_z="0: (1)",
# perlin_init=True,
# perlin_mode="color",
diffusion_sampling_mode='ddim',
max_frames = 50,
width_height = [768, 512],
clip_guidance_scale=7500,
)
Video Input Mode#
text_prompts = "A beautiful new world in Jeju, artstation matte painting."
batch_name = "newworld-video"
disco.imagine(
text_prompts,
batch_name=batch_name,
steps=250,
animation_mode="Video Input",
video_init_path="/workspace/projects/ekorpkit-book/disco-imagen/outputs/disco-diffusion/newworld-3d/newworld-3d(9).mp4",
# rotation_3d_z="0: (1)",
# perlin_init=True,
# perlin_mode="color",
diffusion_sampling_mode='ddim',
max_frames = 10,
width_height = [768, 512],
clip_guidance_scale=7500,
)
INFO:ekorpkit.models.disco.base:warping frames with flow blend ratio: 0.999
INFO:ekorpkit.models.disco.base:Image prompt: []
INFO:ekorpkit.models.disco.base:Frame 4 Prompt: ['A beautiful new world in Jeju, artstation matte painting.']
INFO:ekorpkit.models.disco.base:Seed used: 3402861987
INFO:ekorpkit.models.disco.base: >> elapsed time to diffuse: 0:02:33.218085
INFO:ekorpkit.models.art.base:Saving config to /workspace/projects/ekorpkit-book/disco-imagen/outputs/disco-diffusion/newworld-video/newworld-video(0)_settings.yaml
Create a video from output frames#
batch_name = "newworld-video"
batch_num = 0
mp4_path = disco.create_video(
batch_name=batch_name,
batch_num=batch_num,
)
from IPython.display import Video
Video(mp4_path, embed=True)
collage generated sample images#
disco.collage(
batch_name=batch_name,
batch_num=4,
ncols=2,
num_images=4,
show_filename=True,
fontcolor="black",
)
INFO:ekorpkit.models.dalle.base:Loading config from /workspace/projects/ekorpkit-book/disco-imagen/outputs/disco-diffusion/halla/halla(4)_settings.yaml
INFO:ekorpkit.models.dalle.base:Merging config with diffuse defaults
INFO:ekorpkit.models.disco.base:Will save every 2 steps
INFO:ekorpkit.models.disco.base:Using seed: 221812581
INFO:ekorpkit.models.dalle.base:Prompt: Mt. Halla's beautiful flowers, artstation matte painting
INFO:ekorpkit.io.file:Processing [4] files from ['halla(4)_*.png']
make gif of progresses of a specific sample image#
disco.make_gif(
batch_name='halla',
batch_num=1,
sample_num=1,
show=False,
duration=100,
force_remake=True,
)
Saved GIF to /workspace/projects/ekorpkit-book/disco-imagen/outputs/halla/halla(1)_0001.gif
show config#
disco.show_config(batch_name=batch_name, batch_num=4)
INFO:ekorpkit.models.disco.base:Loading config from /workspace/projects/ekorpkit-book/disco-imagen/outputs/halla/halla(4)_settings.yaml
INFO:ekorpkit.models.disco.base:Merging config with diffuse defaults
INFO:ekorpkit.models.disco.base:Merging config with args: {}
INFO:ekorpkit.models.disco.base:Will save every 2 steps
INFO:ekorpkit.models.disco.base:Using seed: 3370684779
{'angle': '0:(0)',
'animation_mode': 'None',
'batch_name': 'halla',
'batch_num': 7,
'batch_size': 1,
'calc_frames_skip_steps': 150,
'clamp_grad': True,
'clamp_max': 0.05,
'clip_denoised': False,
'clip_guidance_scale': 5000,
'cut_ic_pow': 1,
'cut_icgray_p': '[0.2]*400+[0]*600',
'cut_innercut': '[4]*400+[12]*600',
'cut_overview': '[12]*400+[4]*600',
'cutn_batches': 4,
'display_rate': 20,
'eta': 0.8,
'extract_nth_frame': 2,
'far_plane': 10000,
'force_flow_generation': False,
'fov': 40,
'frames_scale': 1500,
'frames_skip_steps': '60%',
'fuzzy_prompt': False,
'image_prompts': None,
'init_image': 'None',
'init_scale': 1000,
'intermediate_saves': 250,
'intermediates_in_subfolder': True,
'interp_spline': 'Linear',
'key_frames': True,
'max_frames': 1,
'midas_depth_model': 'dpt_large',
'midas_weight': 0.3,
'n_samples': 4,
'near_plane': 200,
'padding_mode': 'border',
'perlin_init': False,
'perlin_mode': 'mixed',
'persistent_frame_output_in_batch_folder': True,
'rand_mag': 0.05,
'randomize_class': True,
'range_scale': 150,
'resume_from_frame': 'latest',
'resume_run': False,
'retain_overwritten_frames': False,
'rotation_3d_x': '0: (0)',
'rotation_3d_y': '0: (0)',
'rotation_3d_z': '0: (0)',
'run_to_resume': 'latest',
'sampling_mode': 'bicubic',
'sat_scale': 0,
'seed': 3370684779,
'set_seed': 'random_seed',
'show_collage': True,
'side_x': 768,
'side_y': 512,
'skip_augs': False,
'skip_steps': 10,
'start_frame': 0,
'steps': 250,
'steps_per_checkpoint': 2,
'stop_on_next_loop': False,
'text_prompts': {0: ["Mt. Halla's beautiful flowers, artstation matte "
'painting'],
100: ['This set of prompts start at frame 100',
'This prompt has weight five:5']},
'transformation_percent': [0.09],
'translation_x': '0: (0)',
'translation_y': '0: (0)',
'translation_z': '0: (10.0)',
'turbo_mode': False,
'turbo_preroll': 10,
'turbo_steps': '3',
'tv_scale': 0,
'use_horizontal_symmetry': False,
'use_vertical_symmetry': False,
'video_init_blend_mode': 'optical flow',
'video_init_check_consistency': False,
'video_init_clip_guidance_scale': 1000,
'video_init_cutn_batches': 4,
'video_init_file': 'init.mp4',
'video_init_flow_blend': 0.999,
'video_init_flow_warp': True,
'video_init_frames_scale': 15000,
'video_init_frames_skip_steps': '70%',
'video_init_path': '/workspace/projects/ekorpkit-book/disco-imagen/init_images/init.mp4',
'video_init_range_scale': 150,
'video_init_sat_scale': 300,
'video_init_seed_continuity': False,
'video_init_skip_steps': 50,
'video_init_steps': 100,
'video_init_tv_scale': 0.1,
'vr_eye_angle': 0.5,
'vr_ipd': 5.0,
'vr_mode': False,
'width_height': [768, 512],
'zoom': '0: (1), 10: (1.05)'}
Model Parameters#
disco.parameters()
{'advanced': {'clamp_grad': "true {type: 'boolean'}",
'clamp_max': "0.05 {type: 'number'}",
'eta': "0.8 {type: 'number'}",
'set_seed': "random_seed {type: 'string'}"},
'advanced_extra': {'clip_denoised': 'false',
'fuzzy_prompt': 'false',
'rand_mag': '0.05',
'randomize_class': 'true'},
'advanced_perlin_init': {'perlin_init': "false {type: 'boolean'} : Perlin "
'init will replace your init',
'perlin_mode': "mixed ['mixed', 'color', 'gray']"},
'animation_2d': {'angle': "'0:(0)' {type: 'string'} : All rotations are "
'provided in degrees.',
'far_plane': "10000 {type: 'number'}",
'fov': "40 {type: 'number'}",
'interp_spline': 'Linear '
"['Linear','Quadratic','Cubic']{type: "
"'string'} : Do not change, currently will "
'not look good.',
'key_frames': "true {type: 'boolean'}",
'max_frames': "10000 {type: 'number'}",
'midas_depth_model': "dpt_large {type: 'string'}",
'midas_weight': "0.3 {type: 'number'}",
'near_plane': "200 {type: 'number'}",
'padding_mode': "border {type: 'string'}",
'rotation_3d_x': "'0: (0)' {type: 'string'}",
'rotation_3d_y': "'0: (0)' {type: 'string'}",
'rotation_3d_z': "'0: (0)' {type: 'string'}",
'sampling_mode': "bicubic {type: 'string'}",
'translation_x': "'0: (0)' {type: 'string'}",
'translation_y': "'0: (0)' {type: 'string'}",
'translation_z': "'0: (10.0)' {type: 'string'}",
'zoom': "'0: (1), 10: (1.05)' {type: 'string'} : # `zoom` is "
'a multiplier of dimensions, 1 is no zoom.'},
'animation_3d_turbo_mode': {'turbo_mode': "false {type: 'boolean'} : (Starts "
'after frame 10,) skips diffusion '
'steps and just uses depth map to '
'warp images for skipped frames. '
'Speeds up rendering by 2x-4x, and '
'may improve image coherence '
'between frames. For different '
'settings tuned for Turbo Mode, '
'refer to the original Disco-Turbo '
'Github: '
'https://github.com/zippy731/disco-diffusion-turbo',
'turbo_preroll': '10 # frames',
'turbo_steps': '"3" ["2","3","4","5","6"] {type: '
'"string"}'},
'animation_3d_vr_mode': {'vr_eye_angle': "0.5 {type: 'number'} : "
'`vr_eye_angle` is the y-axis '
'rotation of the eyes towards the '
'center',
'vr_ipd': "5.0 {type: 'number'} : interpupillary "
'distance (between the eyes)',
'vr_mode': "false {type: 'boolean'} : Enables stereo "
'rendering of left/right eye views '
'(supporting Turbo) which use a different '
'(fish-eye) camera projection matrix. '
"Note the images you're prompting will "
'work better if they have some inherent '
'wide-angle aspect. The generated images '
'will need to be combined into left/right '
'videos. These can then be stitched into '
'the VR180 format. Google made the VR180 '
'Creator tool but subsequently stopped '
"supporting it. It's available for "
'download in a few places including '
'https://www.patrickgrunwald.de/vr180-creator-download. '
'The tool is not only good for stitching '
'(videos and photos) but also for adding '
'the correct metadata into existing '
'videos, which is needed for services '
'like YouTube to identify the format '
'correctly. Watching YouTube VR videos '
"isn't necessarily the easiest depending "
'on your headset. For instance Oculus '
'have a dedicated media studio and store '
'which makes the files easier to access '
'on a Quest '
'https://creator.oculus.com/manage/mediastudio/. '
'The command to get ffmpeg to concat your '
'frames for each eye is in the form: '
'`ffmpeg -framerate 15 -i frame_%4d_l.png '
'l.mp4` (repeat for r)'},
'basic': {'clip_guidance_scale': "5000 {type: 'number'}",
'cutn_batches': "4 {type: 'number'}",
'range_scale': "150 {type: 'number'}",
'sat_scale': "0 {type: 'number'}",
'skip_augs': "false {type: 'boolean'}",
'steps': "250 [25,50,100,150,250,500,1000] {type: 'raw', "
'allow-input: true}',
'tv_scale': "0 {type: 'number'}",
'width_height': "[1280, 768] {type: 'raw'}"},
'coherency': {'frames_scale': "1500 {type: 'integer'} : `frame_scale` tries "
'to guide the new frame to looking like the old '
'one. A good default is 1500.',
'frames_skip_steps': "'60%' ['40%', '50%', '60%', '70%', '80%'] "
"{type: 'string'} : `frame_skip_steps` "
'will blur the previous frame - higher '
'values will flicker less but struggle to '
'add enough new detail to zoom into.'},
'cutn_scheduling': {'cut_ic_pow': "1 {type: 'number'}",
'cut_icgray_p': "'[0.2]*400+[0]*600' {type: 'string'}",
'cut_innercut': "'[4]*400+[12]*600' {type: 'string'}",
'cut_overview': "'[12]*400+[4]*600' {type: 'string'} \n"
'>> Format: `[40]*400+[20]*600` = 40 cuts '
'for the first 400 /1000 steps, then 20 '
'for the last 600/1000. cut_overview and '
'cut_innercut are cumulative for total '
'cutn on any given step. Overview cuts '
'see the entire image and are good for '
'early structure, innercuts are your '
'standard cutn.'},
'init_image': {'init_image': "None {type: 'string'}",
'init_scale': "1000 {type: 'integer'}",
'skip_steps': "10 {type: 'integer'} *Make sure you set "
'skip_steps to ~50% of your steps if you want to '
'use an init image.*'},
'run': {'animation_mode': "None ['None', '2D', '3D', 'Video Input'] "
"{type:'string'}",
'batch_name': "TimeToDisco {type: 'string'}",
'batch_size': '1',
'diffusion_sampling_mode': "ddim ['plms','ddim']",
'display_rate': "20 {type: 'number'}",
'n_samples': "6 {type: 'number'}",
'resume_from_frame': 'latest',
'resume_run': 'false',
'retain_overwritten_frames': 'true',
'run_to_resume': 'latest',
'show_collage': 'true',
'use_secondary_model': 'true'},
'saving': {'intermediate_saves': "0 {type: 'raw'} : Intermediate steps will "
'save a copy at your specified intervals. '
'You can either format it as a single '
'integer or a list of specific steps. A '
'value of `2` will save a copy at 33% and '
'66%. 0 will save none. A value of `[5, 9, '
'34, 45]` will save at steps 5, 9, 34, and '
'45. (Make sure to include the brackets)',
'intermediates_in_subfolder': "true {type: 'boolean'}",
'steps_per_checkpoint': None},
'transformation': {'transformation_percent': '[0.09]',
'use_horizontal_symmetry': "false {type: 'boolean'}",
'use_vertical_symmetry': "false {type: 'boolean'}"},
'video_init': {'video_init_clip_guidance_scale': "1000 {type: 'number'}",
'video_init_cutn_batches': "4 {type: 'number'}",
'video_init_range_scale': "150 {type: 'number'}",
'video_init_sat_scale': "300 {type: 'number'}",
'video_init_skip_steps': "50 {type: 'integer'}",
'video_init_steps': '100 [25,50,100,150,250,500,1000]{type: '
"'raw', allow-input: true}",
'video_init_tv_scale': "0.1 {type: 'number'}"},
'video_init_coherency': {'force_flow_generation': "false {type:'boolean'}",
'video_init_frames_scale': "15000 {type: 'integer'} "
': `frame_scale` tries to '
'guide the new frame to '
'looking like the old '
'one. A good default is '
'1500.',
'video_init_frames_skip_steps': "'70%' ['40%', "
"'50%', '60%', "
"'70%', '80%'] "
"{type: 'string'} : "
'`frame_skip_steps` '
'will blur the '
'previous frame - '
'higher values will '
'flicker less but '
'struggle to add '
'enough new detail '
'to zoom into.'},
'video_init_flow': {'video_init_blend_mode': "optical flow ['None', 'linear', "
"'optical flow'] : Call optical "
'flow from video frames and warp '
'prev frame with flow',
'video_init_check_consistency': 'false',
'video_init_flow_blend': "0.999 {type: 'number'} : 0 - "
'take next frame, 1 - take prev '
'warped frame',
'video_init_flow_warp': "true {type: 'boolean'} : Call "
'optical flow from video frames '
'and warp prev frame with flow'},
'video_init_input': {'extract_nth_frame': "2 {type: 'number'}",
'persistent_frame_output_in_batch_folder': 'true {type: '
"'boolean'}",
'video_init_file': "init.mp4 {type: 'string'}",
'video_init_path': '{..path.init_dir}/{.video_init_file}',
'video_init_seed_continuity': "false {type: 'boolean'}"},
'video_output': {'blend': '0.5',
'fps': '12',
'init_frame': "1 {type: 'number'} : This is the frame where "
'the video will start',
'last_frame': "final_frame {type: 'number'} \n"
'>> You can change i to the number of the last '
'frame you want to generate. \n'
'It will raise an error if that number of '
'frames does not exist.',
'skip_video_for_run_all': 'false',
'video_init_check_consistency': 'false',
'view_video_in_cell': 'false'}}
disco.parameters("display")
[display_rate]
20 {type: 'number'}